An international survey of the structure and process of care for traumatic spinal cord injury in acute and rehabilitation facilities: lessons learned from a pilot study
Bibliographic record
Abstract
Abstract Background To describe the key findings and lessons learned from an international pilot study that surveyed spinal cord injury programs in acute and rehabilitation facilities to understand the status of spinal cord injury care. Methods An online survey with two questionnaires, a 74-item for acute care and a 51-item for rehabilitation, was used. A subset of survey items relevant to the themes of specialized care, timeliness, patient-centeredness, and evidence-based care were operationalized as structure or process indicators. Percentages of facilities reporting the structure or process to be present, and percentages of indicators met by each facility were calculated and reported separately for facilities from high-income countries (HIC) and from low and middle-income countries (LMIC) to identify “hard to meet” indicators defined as those met by less than two-thirds of facilities and to describe performance level. Results A total of 26 acute and 26 rehabilitation facilities from 25 countries participated in the study. The comparison of the facilities based on the country income level revealed three general observations: 1) some indicators were met equally well by both HIC and LMIC, such as 24-hour access to CT scanners in acute care and out-patient services at rehabilitation facilities; 2) some indicators were hard to meet for LMIC but not for HIC, such as having a multidisciplinary team for both acute and rehabilitation settings; and 3) some indicators were hard to meet by both HIC and LMIC, including having peer counselling programs. Variability was also observed for the same indicator between acute and rehabilitation facilities, and a wide range in the total number of indicators met among HIC facilities (acute 59–100%; rehabilitation 36–100%) and among LMIC facilities (acute: 41–82%; rehabilitation: 36–93%) was reported. Conclusions Results from this international pilot study found that the participating acute and rehabilitation facilities on average adhered to 74% of the selected indicators, suggesting that the structure and processes to provide ideal traumatic spinal cord injury care were broadly available. Recruiting a representative sample of SCI facilities and incorporating regional attributes in future surveys will be helpful to examine factors affecting adherence to indicators.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".